The distribution of telomere length in humans is broad, but it has finite upper and lower boundaries. Growing evidence shows that there are disease processes that are caused by both short and long telomere length extremes. The genetic basis of these short and long telomere syndromes may be linked to mutations in the same genes, such as the telomerase reverse transcriptase (TERT), but through differential effects on telomere length. Short telomere syndromes have a predominant degenerative phenotype marked by organ failure that most commonly manifests as pulmonary fibrosis and are associated with a relatively low cancer incidence. In contrast, insights from studies of cancer-prone families as well as genome-wide association studies (GWAS) have identified both rare and common variants that lengthen telomeres as being strongly associated with cancer risk. We have hypothesized that these cancers represent a long telomere syndrome that is associated with a high penetrance of cutaneous melanoma and chronic lymphocytic leukemia. In this Review, we will synthesize the clinical and human genetic observations with data from mouse models to define the role of telomeres in cancer etiology and biology.
Emily J. McNally, Paz J. Luncsford, Mary Armanios
Usage data is cumulative from January 2024 through January 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 1,800 | 1,056 |
244 | 128 | |
Figure | 255 | 10 |
Table | 71 | 0 |
Citation downloads | 87 | 0 |
Totals | 2,457 | 1,194 |
Total Views | 3,651 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.